Question: How do you handle data skew in a distributed computing environment?

Answer: Data skew occurs when certain partitions or shards have significantly more data than others. Techniques to handle data skew include re-partitioning, data pre-processing, and using advanced algorithms for data distribution.

Example:

Re-partitioning a dataset based on a different key to distribute the data more evenly in a Spark job.